Project summary This project proposes to study mechanisms of synaptic processing within specific ganglion cell types in the mammalian retina, both by direct electrophysiological recording and through the use of realistic computer models. Retinal ganglion cells are the output neurons of the retina. There are around 20-30 types of retinal ganglion cell in a typical mammalian retina, with each type optimized to detect different features in the visual scene. Each retinal ganglion cell type is present as an orderly array of cells that cover the entire retina, and therefore the concerted activity of each ganglion cell type represents a separate version of the visual image. Thus, the brain simultaneously receives 20-30 distinct images that it combines within central visual areas to produce a continuous, coherent model of the visual world. This project focuses on a specific type of retinal ganglion cell that signals direction of motion, called the direction-selective ganglion cell (DSGC). Recordings from DSGCs from in-vitro isolated retina preparations in mouse and rabbit will be used to characterize the electrical and morphological properties of these cells. Realistic computational models of the neural circuitry will be generated based on this information. Recapitulation of the real responses by the model system will be used to test our understanding of the underlying neural circuits. The study comprises three sections. Aim 1 examines the function of the starburst amacrine cell (SBAC), an interneuron that is the source of direction selective inhibitory inputs to the DSGC. This aim tests the hypothesis that several mechanisms in SBAC dendrites generate and amplify the direction-selective inhibitory signal. The computer model of the SBAC circuit will include sodium and calcium channels in a network of SBACs that are interconnected by reciprocal inhibition. Aim 2 tests the hypothesis that surround inhibition modulates the strength and spatial and temporal resolution of the synaptic input to the DSGC. The experimental results will be used to extend the computer model to take into account the inhibitory inputs from amacrine cells that integrate information over larger regions of the visual scene surrounding the DSGC. Aim 3 examines the reliability in the spiking output of the DSGC, and how this is affected by the presence of ambiguities and noise in the visual input. The data obtained will be used to further develop the computer model to simulate DSGC spike responses. The final model, based on physiological results from all three Aims, will represent a detailed, and essentially complete representation of the neural mechanisms involved in directional signalling in the mammalian retina. If successful, the model should reproduce realistic spiking output for any visual stimulus. Overall, the proposed research will improve our understanding of the complex circuitry of the adult retina; the knowledge gained will inform continuing efforts to develop treatments and visual prosthetic devices that restore vision loss from a range of eye diseases.